• 한국지반환경공학회 논문집
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• 제2권4호
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• pp.51-61
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• 2001

본 논문에서는 지반의 상대다짐도(RC)와 매입말뚝의 근입비에 따른 하중-침하 거동을 연구하기 위하여 모형실험과 하중전이 함수를 이용한 해석을 수행하였다. 모형시험에서 말뚝은 근입비(L/D)를 15, 20, 25로 설치하였고, 지반의 상대다짐도를 85%, 95%로 각각 조성하였으며 말뚝주면은 시멘트를 주입하였다. 본 논문은 매입말뚝의 해석을 위하여 Vijayvergia의 하중전이 모델, Castelli 모델, Gwizdala의 탄소성-완전소성 모델, coyle의 제안식 등을 사용하여 실험결과와 비교하였으며, 매입말뚝의 하중-침하 거동을 예측하는데 가장 적합한 하중전이 방법을 제안하였다. 하중전이 함수에 의한 지지력 예측 결과 매입말뚝의 극한 지지력은 Coyle의 제안식이 실측값에 가장 근접한 것으로 나타났으며, 초기 하중-침하 거동은 Castelli에 의한 함수가 가장 유사하게 하중-침하 거동을 평가하는 것으로 나타났다. 매입말뚝의 축하중 해석결과 하중전이법에 의해 평가된 주면마찰력이 실측값보다 과소평가 되는 것으로 나타났다.

• 천문학회보
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• 제36권2호
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• pp.151.2-151.2
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• 2011

IGRINS (Immersion GRating INfrared Spectrometer) will provide the spectra with high-resolution and an instantaneous spectral coverage of H and K band in NIR region. Therefore, it is expected that the wide coverage of wavelength would make a production of an extensive NIR high-resolution spectra of standard stars as a prior program of IGRINS. As a counter part of these NIR spectra, we have planned to obtain the high-resolution spectra of those standard stars in optical band. These optical high-resolution spectra would give us an opportunity to produce the library of high-resolution stellar spectra covering from optical to NIR band, and to confirm the method to determine the stellar parameters and chemical abundances from the NIR high-resolution spectra. Before using the NIR high-resolution spectra, we have tested the method to determine the stellar parameters by comparing between the observed spectra and the synthetic spectra in optical band. In order to make the synthetic spectra, we have used the Kurucz ATLAS9 model grids and the SYNTH code described by Fiorella Castelli (http://wwwuser.oat.ts.astro.it/castelli/). For the cross-check against the parameters that would be derived from the NIR spectra, the stellar parameters such as effective temperature and surface gravity were determined using the optical spectra of the solar-like stars, as preliminary results.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.92-96
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• 2004

The researches of the emotions are currently great interest in speech processing as well as in human-machine interaction domain. In the recent years, more and more of researches relating to emotion synthesis or emotion recognition are developed for the different purposes. Each approach uses its methods and its various parameters measured on the speech signal. In this paper, we proposed using a short-time parameter: MFCC coefficients (Mel­Frequency Cepstrum Coefficients) and a simple but efficient classifying method: Vector Quantification (VQ) for speaker-dependent emotion recognition. Many other features: energy, pitch, zero crossing, phonetic rate, LPC... and their derivatives are also tested and combined with MFCC coefficients in order to find the best combination. The other models: GMM and HMM (Discrete and Continuous Hidden Markov Model) are studied as well in the hope that the usage of continuous distribution and the temporal behaviour of this set of features will improve the quality of emotion recognition. The maximum accuracy recognizing five different emotions exceeds $88\%$ by using only MFCC coefficients with VQ model. This is a simple but efficient approach, the result is even much better than those obtained with the same database in human evaluation by listening and judging without returning permission nor comparison between sentences [8]; And this result is positively comparable with the other approaches.

• Computers and Concrete
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• 제19권6호
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• pp.651-658
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• 2017

High-performance concrete, besides aggregate, cement, and water, incorporates supplementary cementitious materials, such as fly ash and blast furnace slag, and chemical admixture, such as superplasticizer. Hence, it is a highly complex material and modeling its behavior represents a difficult task. This paper presents an evolutionary system for the prediction of high performance concrete strength. The proposed framework blends a recently developed version of genetic programming with a local search method. The resulting system enables us to build a model that produces an accurate estimation of the considered parameter. Experimental results show the suitability of the proposed system for the prediction of concrete strength. The proposed method produces a lower error with respect to the state-of-the art technique. The paper provides two contributions: from the point of view of the high performance concrete strength prediction, a system able to outperform existing state-of-the-art techniques is defined; from the machine learning perspective, this case study shows that including a local searcher in the geometric semantic genetic programming system can speed up the convergence of the search process.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.237-243
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• 2004

A multichannel smart sound sensor capable to detect and identify sound events in noisy conditions is presented in this paper. Sound information extraction is a complex task and the main difficulty consists is the extraction of high­level information from an one-dimensional signal. The input of smart sound sensor is composed of data collected by 5 microphones and its output data is sent through a network. For a real time working purpose, the sound analysis is divided in three steps: sound event detection for each sound channel, fusion between simultaneously events and sound identification. The event detection module find impulsive signals in the noise and extracts them from the signal flow. Our smart sensor must be capable to identify impulsive signals but also speech presence too, in a noisy environment. The classification module is launched in a parallel task on the channel chosen by data fusion process. It looks to identify the event sound between seven predefined sound classes and uses a Gaussian Mixture Model (GMM) method. Mel Frequency Cepstral Coefficients are used in combination with new ones like zero crossing rate, centroid and roll-off point. This smart sound sensor is a part of a medical telemonitoring project with the aim of detecting serious accidents.